CQ Elite

CQ Elite allows you to take your backtesting of trading strategies and trading algorithms to the next level.

You have ideas, thoughts, insights on how to create a profitable trading strategy. But you know that to be effective, to be profitable in quantitative trading you need:

Access to historical market data

Access to technology

Access to traders

Access to capital

Access to new datasets

Access to strategy backtesting tools

Access to the professional level, standardized reports

CQ Elite provides you all of this. It is an environment where you can confidentially test your trading ideas or strategies by having access to more detailed trade and quote data.

The backtest homepage on CloudQuant allows you to compare, interact, and download key statistics on your quantitative research.

Market Data Available in CQ Elite

Millisecond level Historical Market Data.

askvol: The sum of the volume traded shares at or above the ask during the timeframe

avgdelta: Average change in price between trades during time period.

bidvol: The sum of the volume traded shares at or below the bid during the timeframe

bvwap: the volume weighted average price

close: the closing price for the bar

count: number of items contributing to the bar

high: the highest price for the bar interval

length: integer time length for the bar

low: lowest price for the bar

open: first qualifying trade of the bar

primary_close: closing price for the symbol’s primary exchange

primary_open: opening price for the symbol’s primary exchange

spread: The average difference between the ask and the bid for the bar

symbol: the exchange mnemonic that represents one exchange trade stock or other financial instruments.

timestamp: The timestamps for the beginning

valid: whether or not bar is valid

volume: The volume for the bar

vwap: volume-weighted average price(vwap)

NYSE, ARCA, and NASDAQ imbalance data

Earnings calenders

News sentiment data

Historical Statistics on each symbol including:

atr: Average True Range (a.k.a. Average Trading Range), over 10 days based on an underlying 250 days of TR (True Range).

avol: Average Volume over 21 days, or whatever smaller number of days is actually available.

beta: Beta, computed over a 249 day time period or as short as 20 days

dividend_amount: The dividend amount in dollars applied to the stock price.

dividend_comment: further information on the dividend

exchange: The primary exchange code

lot_size: number of shares per lot

prev_close: the previous day’s closing price

Data is not directly accessible. The only way to access the data is through a backtest script.

Sentiment Data Available in CQ Elite

Sentiment is a score or ranking of how a group of investors or investment professionals “feel” about news and investments. The sentiment comes from multiple sources: Twitter, Blogs, LinkedIn, Facebook, etc. Some sentiment is from market professionals or their Artificial Intelligence equivalents that monitor news stories, public filings, speeches, or other public sources.

The sentiment is quantified on a range from pessimistic to optimistic about the company or the specific news.

Sentiment Data is often referred to as Emerging Data, Alternative Data or AltData.

CloudQuant Elite has Sentiment data for:

Social Media Analytics

Alexandria Technologies

Data is not directly accessible. The only way to access the data is through a backtest script.

Fundamental and Estimate Data

Additional data sets are being on boarded including Fundamental and Estimate data.

Backtesting

Backtesting provides a way to evaluate your trading strategy based on historical data to estimate the how the strategy would perform. Historically this has only been possible within large financial institutions with access to large data sets, and computer infrastructure.

CloudQuant is breaking that mold and using modern cloud technology to level the playing field.

Elite members have backtesting access to more advanced functions within their scripts. These allow the algo to be more sophisticated. For example, the “on_nbbo_price” function allows you to develop a better profit taking algo by providing you with access to each best bid and best offer change rather than having to wait for each 1-minute bar change that is available in CQ Lite.

Elite Backtest Functions include:

Order Processing Events:

on_ack,

on_fill,

on_cancel,

on_reject

Market Data Events

on_nasdaq_imbalance,

on_nyse_imbalance,

on_nbbo_price,

on_trade,

on_arca_imbalance,

As a CQ Elite user, you are able to run as many backtest as you require to validate that your trading strategy will work. You are in control. You can choose:

The Date range,

The symbols,

The parameters,

The Latency

The Risk Management

The Input Data

Backtest results are shown online. As a CQ Elite user, you have access to multiple reports and statistics on your trading strategies.

Backtest Scorecard as seen on CloudQuant

Quantitative Trading Strategy Portfolio Heatmap

Technology

The CQ Elite platform is a cloud-based environment that supports Python.

Python is easy to use, robust and forgiving programming language. Many people who have written macros in Microsoft Excel® have a very easy time learning Python.

CloudQuant provides access to several popular financial and statistical libraries.

Stock Trading Minute Bar with Entry and Exit on CloudQuant

The thoughts and opinions on this site do not represent investment recommendations by CloudQuant or Kershner Trading Group. Securities, charts, illustrations and other information contained herein are provided to assist crowd researchers in their efforts to develop algorithmic trading strategies for backtesting on CloudQuant.